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Show HN: GovernsAI – unified auth, memory, and PII guard across AI providers

Hacker News - Thu, 03/05/2026 - 1:34pm

I built GovernsAI to solve a problem I kept hitting while switching between OpenAI, Anthropic, and Google: no shared memory, no centralized access control, and PII leaking into prompts constantly.

It's essentially an AI OS layer that sits above the providers:

- Unified authentication across OpenAI, Anthropic, Google - Persistent memory management that follows you across models - A precheck service that catches PII before it hits any API - Budget enforcement and human-in-the-loop confirmation workflows - A browser extension (pii-guard) that intercepts at the input level

The architecture is documented in a paper I submitted to arXiv if you want to go deep on the design decisions.

Happy to answer questions about the infra choices, the memory layer, or why I built on top of providers instead of picking one.

https://governsai.com

Github: https://github.com/Governs-AI

Comments URL: https://news.ycombinator.com/item?id=47265365

Points: 1

# Comments: 0

Categories: Hacker News

SN 1068: The Call Is Coming From Inside the House - Live From Zero Trust World 2026

Security Now - Thu, 03/05/2026 - 1:25pm

Steve Gibson and Leo Laporte host a special episode of Security Now live from ThreatLocker's Zero Trust World 2026 in Orlando, Florida.

The final frontier of security is internal. Today, we have the tools, techniques and technologies to thwart attacks originating from outside our perimeter. We're now good at protecting our borders. But major high profile breaches occurring over the past several years have revealed that insufficient attention has been given to the security of our internal systems and networks. Today's greatest security weaknesses result from decades of system design, deployment and policy that have placed far too much trust on the conduct of those on the inside, behind our borders. Whether deliberate, inadvertent, or externally penetrating, the greatest challenge we now face is that of designing and deploying our internal security with strict adherence to the principles of least privilege and zero trust.

Hosts: Steve Gibson and Leo Laporte

Download or subscribe to Security Now at https://twit.tv/shows/security-now.

You can submit a question to Security Now at the GRC Feedback Page.

For 16kbps versions, transcripts, and notes (including fixes), visit Steve's site: grc.com, also the home of the best disk maintenance and recovery utility ever written Spinrite 6.

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Categories: Security Now

New ChatGPT 5.4 Model Is 'Built for Agents.' Will It Lure Back Claude Converts?

CNET Feed - Thu, 03/05/2026 - 1:00pm
OpenAI has new AI models for the second time this week.
Categories: CNET

Olmo Hybrid

Hacker News - Thu, 03/05/2026 - 12:45pm
Categories: Hacker News

Show HN: Plought – Reduce noise in decision making

Hacker News - Thu, 03/05/2026 - 12:45pm

Just launched the revamped Plought: a decision-making app to compare options with structured methods. This version includes new tools and summarized analysis based on your inputs.

Use it for hard choices like where to move, which job to take, or what car to buy.

Free, no login, and open source.

Your data stays private in your browser’s local storage, with export available.

Try it: https://plought.app/

Code: https://github.com/rossrobino/plought

Feedback welcome!

Comments URL: https://news.ycombinator.com/item?id=47264764

Points: 1

# Comments: 0

Categories: Hacker News

Everything Apple Announced This Week, From iPhone 17E to MacBook Neo

CNET Feed - Thu, 03/05/2026 - 12:45pm
Devices have been flying out of Cupertino the past three days, and everything's up for preorder now. Here's what's new.
Categories: CNET

The Brand Age

Hacker News - Thu, 03/05/2026 - 12:44pm

Article URL: https://paulgraham.com/brandage.html

Comments URL: https://news.ycombinator.com/item?id=47264756

Points: 2

# Comments: 0

Categories: Hacker News

Launch HN: Vela (YC W26) – AI for complex scheduling

Hacker News - Thu, 03/05/2026 - 12:43pm

Hi HN! We're Gobhanu and Saatvik (brothers), building Vela (https://tryvela.ai) - AI agents that handle multi-party, multi-channel scheduling.

Scheduling is a constraint satisfaction problem disguised as email! It’s easy when it’s two people, one timezone, one channel. But it becomes a constraint satisfaction problem when inputs are unstructured natural language across multiple communication channels, constraints change mid-solve, and the objective function includes social dynamics that don't exist formally anywhere.

What if scheduling just happened? For example: a recruiter sends one message, and every interview across five candidates, three hiring managers, and two time zones gets booked, confirmed, and updated automatically. No links, no back-and-forth, no one spending hours with 20 emails. Everyone just gets the right invite at the right time, on whatever channel they actually use. That's what we built Vela to do.

You loop in Vela into your emails, SMS, WhatsApp, Slack, phone or integrate into an ATS etc and it takes over: reads context, checks calendars, proposes times, follows up when people ghost, and rebooks when things shift.

One of our first customers is a staffing firm that searched for a scheduling solution for almost eight years. Their coordinators manage hundreds of candidate-client interviews where each side needs separate email threads, separate Zoom accounts to avoid double-booking links, and calendar invites connecting parties who never directly communicate. A client reschedules one interview and it cascades into four others. A candidate responds on SMS to a thread that started on email. Vela solved this in just 10 minutes of onboarding.

The hardest part has been the data problem. Scheduling behavior varies enormously across populations. C-suite folks respond to email within hours and expect formal 3-option proposals. Truck drivers applying for logistics roles respond to SMS at odd hours from shared devices with "y tm wrks." The failure mode isn't parsing -- it's applying the wrong interaction pattern for the wrong segment and watching the conversation die. We've been building behavioral datasets from thousands of real interactions: response latency by role, channel preference by demographic, follow-up timing curves, how many options to propose before you hit decision paralysis. This data doesn't exist anywhere.

The core agent challenge is state across channels. When someone responds on SMS to a thread that started in email, Vela needs to unify identity, merge context, and continue without losing information. Phone numbers don't map cleanly to emails, people use nicknames on text, shared devices mean the responder might not be who you reached out to. Temporal NLU is its own problem -- "next Friday" means different things on Monday versus Thursday. We extract structured constraints from natural language and resolve against calendar state. When ambiguity can't be resolved, Vela asks -- but deciding when to ask versus infer depends on the stakes of getting it wrong.

We're live with paying enterprise customers and every client still surfaces edge cases that surprise us. Case studies on our site (https://tryvela.ai/case-studies/). You can check out a demo here: https://www.youtube.com/watch?v=MzUOjSG5Uvw.

We'd love feedback from anyone who's worked on multi-agent coordination, conversational AI across channels, or constraint satisfaction in messy real-world domains. Looking forward to your comments :)

Comments URL: https://news.ycombinator.com/item?id=47264741

Points: 1

# Comments: 0

Categories: Hacker News

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